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Population genetic screening efficiently identifies carriers of autosomal dominant diseases

Nature Medicine volume 26, pages 1235–1239 (2020)Cite this article

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Abstract

Three inherited autosomal dominant conditions—BRCA-related hereditary breast and ovarian cancer (HBOC), Lynch syndrome (LS) and familial hypercholesterolemia (FH)—have been termed the Centers for Disease Control and Prevention Tier 1 (CDCT1) genetic conditions, for which early identification and intervention have a meaningful potential for clinical actionability and a positive impact on public health1. In typical medical practice, genetic testing for these conditions is based on personal or family history, ethnic background or other demographic characteristics2. In this study of a cohort of 26,906 participants in the Healthy Nevada Project (HNP), we first evaluated whether population screening could efficiently identify carriers of these genetic conditions and, second, we evaluated the impact of genetic risk on health outcomes for these participants. We found a 1.33% combined carrier rate for pathogenic and likely pathogenic (P/LP) genetic variants for HBOC, LS and FH. Of these carriers, 21.9% of participants had clinically relevant disease, among whom 70% had been diagnosed with relevant disease before age 65. Moreover, 90% of the risk carriers had not been previously identified, and less than 19.8% of these had documentation in their medical records of inherited genetic disease risk, including family history. In a direct follow-up survey with all carriers, only 25.2% of individuals reported a family history of relevant disease. Our experience with the HNP suggests that genetic screening in patients could identify at-risk carriers, who would not be otherwise identified in routine care.

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Fig. 1: Clinical features of individuals with a P/LP variant in one of the CDCT1 genomic conditions.
Fig. 2: Individuals who likely fall within existing clinical guidelines for genetic testing have a risk of clinically relevant disease in excess of the risk conferred by carrying a P/LP variant alone.

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Data availability

The data that support the findings of this study are available from the corresponding authors.

Code availability

The code that supports the findings of this study is available from the corresponding authors upon reasonable request.

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Acknowledgements

J.J.G., G.E., E.S., K.A.S., R.R., W.J.M., B.L. and H.R. were supported by grants from the Nevada Governor’s Office of Economic Development Knowledge Fund (no. 14685) and by Renown Health (no. GR09183). We thank all participants in the HNP. We also thank the operational teams of the HNP and Helix.

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Authors and Affiliations

  1. Renown Health, Reno, NV, USA

    J. J. Grzymski, C. Rowan, N. Slotnick & A. Slonim

  2. Desert Research Institute, Reno, NV, USA

    J. J. Grzymski, G. Elhanan, E. Smith, K. A. Schlauch, R. Read, S. Dabe, W. J. Metcalf, B. Lipp & H. Reed

  3. Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA

    J. A. Morales Rosado & M. Ferber

  4. Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

    J. A. Morales Rosado & M. Ferber

  5. Helix, San Mateo, CA, USA

    L. Sharma, E. Levin, J. Kao, M. Rashkin, J. Bowes, K. Dunaway, N. Washington, A. Bolze & J. T. Lu

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Contributions

J.J.G., G.E., A.S., A.B. and J.T.L. conceived the presented idea and contributed to the analysis and manuscript writing. J.A.M.R. and M.F. performed P/LP variant interpretation for all participants. C.R., N.S., E.L. and L.S. contributed clinical oversight and clinical data gathering. E.S., K.A.S., J.K., W.J.M., S.D., H.R., B.L., M.R., J.B., K.D. and N.W. helped to organize both clinical and genomic data and execution of the study. J.J.G. and J.T.L. oversaw the overall program. All authors provided critical feedback and helped to shape the research, analysis and manuscript.

Corresponding authors

Correspondence to J. J. Grzymski or J. T. Lu.

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Competing interests

L.S., E.L., J.K., M.R., J.B., K.D., N.W., A.B. and J.T.L. are employees of Helix. J.J.G., G.E., J.A.M.R., K.A.S., R.R., C.R., N.S., S.D., W.J.M., B.L., H.R., A.S. and M.F. declare no competing interests.

Additional information

Peer review information Michael Basson was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Carrying a P/LP variant in a FH gene leads to increased risk and earlier onset of hyperlipidemia and treatment with anti-hyperlipidemic medications.

Disease-free survival for ‘carriers’ (n = 73) of a FH P/LP variant and ‘non-FH carriers’ (n = 20,117) for a, first report of a ICD-10 code for hyperlipidemia in the medical record, and b, first order for an anti-hyperlipidemic medication in the medical record. Solid colored lines (and the matching shaded regions) are survival curves with 95% confidence intervals. The dotted lines represent the median survival age. p-values represent the results of a 2-sided log-rank test. No adjustments were made for multiple comparisons.

Extended Data Fig. 2 Empirical cumulative distribution for age of first diagnosis for P/LP carriers with relevant disease diagnoses.

Clinical relevant disease manifestation for at-risk carriers in our cohort occurs between the ages of 24 and 80, with approximately 40% of disease occurring before the age of 50.

Extended Data Fig. 3 Comparison of the clinical impact of P/LP variants in different genes for the same CDC Tier1 genomic condition.

a-d, Disease-free survival (DFS) for carriers (n = 273) in the Healthy Nevada Project for individuals with medical records at Renown Health. Data are shown for P/LP variant carriers for BRCA1 (n = 54) and BRCA2 (n = 81) for HBOC (a), for P/LP variant carriers for MSH6 (n = 23) and PMS2 (n = 32) for all-cause cancers. There was not sufficient data to explore MLH1 or MSH2 independently (b), for P/LP variant carriers for APOB (n = 14) and LDLR (n = 58) for presentation of hyperlipidemia and (d) for treatment with anti-hyperlipidemic medication. There was not sufficient data to explore PCSK9 independently. Solid colored lines (and the matching shaded regions) are survival curves with 95% confidence intervals. The dotted lines represent the median survival age. p-values represent the results of a 2-sided log-rank test. No adjustments were made for multiple comparisons.

Extended Data Fig. 4 Individuals who likely fall within existing FH clinical guidelines do not have risk in excess of carrying a P/LP variant.

Disease-free survival (DFS) for carriers (n = 273) that likely fall ‘within guidelines’ and those ‘outside guidelines.’ Data are shown for within guidelines (n = 10) vs outside guidelines (n = 63) for FH P/LP variant carriers for presentation of hyperlipidemia a, and for treatment with anti-hyperlipidemic agents b. Solid colored lines (and the matching shaded regions) are survival curves with 95% confidence intervals. The dotted lines represent the median survival age. p-values represent the results of a 2-sided log-rank test. No adjustments were made for multiple comparisons.

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Grzymski, J.J., Elhanan, G., Morales Rosado, J.A. et al. Population genetic screening efficiently identifies carriers of autosomal dominant diseases. Nat Med 26, 1235–1239 (2020). https://doi.org/10.1038/s41591-020-0982-5

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